Method of and arrangement for optimizing and checking heart diagnosis

ABSTRACT

Heart/brain disease is non-invasively, accurately diagnosed at an early stage. A plurality of functions descriptive of the patient are mathematically determined. A set of indices for each function is established in advance. Each index has two states indicative of the patient&#39;s condition. An integrated pattern of the states of the indices from a plurality of the functions is generated and matched against a stored collection of index patterns whose diagnosis is known. The diagnosis is optimized with the aid of weighting factors for such parameters as patient&#39;s age and medical history. In addition, the diagnosis is also checked doctors&#39; opinion.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 07/822,525, filed Jan. 17, 1992, and now abandoned which, inturn, is a continuation-in-part of U.S. patent application Ser. No07/397,695 filed Oct. 30, 1989, now abandoned, and is acontinuation-in-part of U.S. patent application Ser. No. 07/794,502,filed Nov. 19, 1991, now abandoned, and in addition, is acontinuation-in-part of U.S. patent application Ser. No. 08/000,009,filed Jan. 4, 1993, now U.S. Pat. No. 5,394,884.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention generally relates to a method of, and an arrangement for,diagnosing a condition of a patient and, more particularly, to thediagnosis and the optimization of the diagnosis of heart disease inhuman patients.

2. Description of the Related Art

Heart disease are still the leading causes of death around the world.Conventional detection of such disease relies on electrocardiograph(EKG) devices for measuring heart wave activity by sensing electricalsignals at various sites on the human body, and by recording thesesignals as waveforms. A cardiologist evaluates the EKG waveforms todetermine abnormalities therein. Such evaluation requires considerabletraining and skill. Even despite a high degree of training and skill, anEKG waveform can still be interpreted as indicating normal heartactivity even in the presence of advanced coronary artery disease.Experience has shown that conventional EKG devices, although useful, arenot sufficiently reliable to diagnose heart disease, either due toinsufficient sensitivity or specificity, and certainly not at an earlystage of heart disease. It has been estimated that over 50% of peoplewith occlusive coronary artery disease have been reported to have normalEKG waveforms.

The prior art has proposed several approaches to extract moreinformation from the EKG/EEG signals. U.S. Pat. No. 4,924,875 teachesthe extraction of information regarding ischemia, propensity toventricular tachycardia and other disorders in the heart which affectcardiac electrical activity.

In the EKG field, such functions as the frequency content of the EKGsignals, e.g. power spectrum, and the amplitude histogram, e.g.occurrence frequency, have been analyzed. However, in each case, usuallya small portion of one cycle of the processed EKG/EEG signal has benignutilized. This has proven to be an unreliable diagnostic tool.

EKG signals arise from the discharge of electrical potentials fromhundreds of thousands of electrically active cells, thereby resulting ina complex resultant signal. Isolated signal processing analysis of smallportions of the processed EKG signal does not produce reliable data. Theanalysis of a single function characteristic of the EKG/EEG signalsimply does not produce efficient or reliable information. Conventionaltime and frequency domain analysis of the EKG signal, as well as theanalysis of isolated minor portions of single functions of the EKGsignal, fail to address information regarding non-linearities as well ascross correlation, coherence and phase angle over time. The joint effectof all these functions, particularly over an extended test period ofmany test cycles; has not been considered. As a result, the early andreliable detection of heart disease, as well as the specific diagnosisof the type of heart disease, are not presently available, particularlyat a time when the chronic disease might be treated and its progressretarded or halted.

SUMMARY OF THE INVENTION

1. Objects of the Invention

It is a general object of this invention to advance the state of thediagnostic art for detecting heart disease.

Another object of this invention is to detect heart disease at an earlystage in its progress.

Still another object of this invention is to non-invasively andaccurately diagnose heart disease.

A further object of this invention is to diagnose different types ofheart disease.

Another object of this invention is to optimize the diagnosis ofdifferent types of heart disease.

Another object of this invention is for remotely diagnosing the patient.

Yet another object of this invention is for optimizing and checking thediagnosis with patients' history information and doctors' experience tomake the diagnosis more accurate.

2. Features of the Invention

In keeping with these objects and others, which will become apparenthereinafter, one feature of this invention relates, in its broadestaspect, to determining a condition of a sample by acquiring electricalanalog signals from the sample. In one preferred embodiment, the signalsare EKG signals obtained from a surface of the body of a patient byplacement of a plurality of surface electrodes at various sites thereon.

The method and arrangement of this invention, however, are not intendedto be limited to the determination of heart disease from EKG signals, orof brain disease from EEG signals. This invention can be extended to theanalysis of any biological signals generated during the course of suchmedical examinations as an electromyogram, electrobasogram,electrocorticogram, electrocystogram, electrogastrogram,electrometrogram, electronystagmogram, electro-oculogram,electroretinogram, electrospinogram, etc. In addition, the method andarrangement of this invention can be extended to the analysis ofnon-biological signals, e.g. physical signals or chemical signals,obtained during the course of measurement in a seismogram,eletrophoretogram, thermogram, etc.

This invention processes the analog signals, whether biological or not,and mathematically determines a plurality of functions descriptive ofthe sample being analyzed. Thus, in the case of EKG signals, thefunctions include, as described in detail below, the power spectrumcharacteristic, the coherence characteristic, the phase anglecharacteristic, the impulse response characteristic, the crosscorrelation characteristic and the amplitude histogram characteristic.Each of these functions carries a wealth of different information aboutthe EKG signals, particularly when the functions are processed over anextended time period which, in the preferred embodiment, is 15 cycleslasting 10 seconds per cycle. The extended time period is many orders ofmagnitude greater than the typical analysis of EKG signals which, atbest, process a minor fraction of one heart cycle of a heart functioncharacteristic.

In accordance with this invention, a set of indices is established foreach function. Each index has two states. The positive state indicatesan abnormal condition for the sample. A negative state indicates anormal condition. The indices generally relate to the pattern or shapeof the waveform of each function characteristic. As described in detailbelow, the preset indices include the magnitude of peaks, the intervalsbetween peaks, the curvature of the peaks, the number of bends, etc.

An integrated index pattern of the states of the indices derived from aplurality, if not all, of the functions is generated. This integratedpattern is then matched against a stored collection of index patternswhose condition (i.e., diagnosis) is known. The best match thendetermines the diagnosis for the patient being analyzed.

The collection of stored index patterns is based on storing the indexpatterns of a multitude, e.g., many thousands, of patients whosecondition is known and whose condition was confirmed by medicalexamination and testing. Thus, patients having myocarditis, for example,have index patterns which, when grouped together, have a distinctivepattern. Patients having a different heart disease have differentlydistinctive index patterns. As previously mentioned, the index patternof the patient being tested is compared to each group of known patternsto find the best match and, hence, the diagnosis.

In the case of a cardiac patient, the collection of stored indexpatterns are advantageously grouped into the following eight categories:coronary heart disease, rheumatic heart disease, pulmonary heartdisease, congenital heart disease, myocarditis, myocardiopathy,fibrillation and ventricle hypertrophy. This invention thus can matchthe cardiac patient's measured pattern against the patterns of thesecategories to select the one that best describes the patient's cardiaccondition.

The number of matching indices compared to the total number of indicesin the integrated index pattern is determined and, when multiplied by100%, is called the "score" or "raw score". In the preferred embodiment,the two categories of heart disease having the two highest scores arepresented to the physician for suggested use in deciding upon the finaldiagnosis.

Prior to presentation of suggested diagnoses to the physician, variousweighting factors are used to optimize the suggested diagnoses. Forexample, in the aforementioned case of a cardiac patient, the patient'sage is a contributing factor and, hence, is used to modify the rawscores to achieve so-called "weighted scores" for presentation to thephysician.

Factors, other than age, can be used. For example, the patient's knownmedical history is a significant parameter.

In addition, in this invention, doctors' opinion, as one of the factors,can be used to input into the machine, and modify the out-put(diagnosis) of the machine to make the diagnosis more accurate.

Hence, rather than relying on data extracted over a limited time for asingle function, this invention relies on data extracted over anextended time from a plurality of functions, some of which have notheretofore been used in the diagnosis of heart disease.

The novel features which are considered as characteristic of theinvention are set forth in particular in the appended claims. Theinvention itself, however, both as to its construction and its method ofoperation, together with additional objects and advantages thereof, bestwill be understood from the following description of specificembodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a front view of an arrangement in accordance with the methodof this invention;

FIG. 2 is a block diagram of the arrangement of FIG. 1 connected to apatient;

FIG. 3 is an electrical schematic diagram of the EKG combiner networkdepicted in FIG. 2;

FIG. 4 is an overall block diagram of the signal processor depicted inFIG. 2;

FIG. 5 is an EKG waveform from the left ventricular lead of a patientunder test;

FIG. 6 is a graph of the power spectrum characteristic of the waveformof FIG. 5;

FIG. 7 is a graph analogous to FIG. 6 but of the EKG waveform from thewhole heart lead;

FIG. 8 is a graph of the phase angle characteristic of the patient undertest;

FIG. 9 is a graph of the impulse response characteristic of the patientunder test;

FIG. 10 is a graph of the amplitude histogram characteristic from theleft ventricular lead of the patient under test;

FIG. 11 is a graph analogous to FIG. 10 but from the whole heart lead;

FIG. 12 is a graph of the coherence characteristic of the patient undertest;

FIG. 13 is a graph of the cross correlation characteristic of thepatient under test;

FIG. 14 is a sample print-out of a cardiogram analysis for the patientunder test;

FIG. 15 is a flow chart depicting an improvement in the signal processorof FIG. 4;

FIG. 16 is a flow chart depicting another improvement in the signalprocessor of FIG. 4;

FIG. 17 is a block diagram depicting a remote signal processor system;and

FIG. 18 is a flow chart depicting part of the operation of the system ofFIG. 17.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Referring now to the drawings, reference numeral 10 generally identifiesan arrangement for diagnosing heart/brain disease in accordance with themethod of this invention. Arrangement 10 includes a keyboard 12 formanual data entry and operational control, a monitor 14 for displayingand plotting data and a printer 16 for printing a written data record.As described below, electronic circuitry within the arrangement isemployed to process EKG or EEG signals in order to obtain a diagnosis ofa condition of a patient 18.

In the case of diagnosing heart disease, the arrangement 10 is connectedto the patient by a cable set 20 in a conventional EKG hook-up. Thecable set 20 includes five wires each having a surface electrodepositioned at various fixed sites on the patient's body. As depicted inFIG. 3, an electrode 22 connected to a conventional EKG "white" wire isplaced over the area of the patient's body overlying the left ventricle.An electrode 24 connected to a conventional EKG "yellow" wire is placedover the left hand. An electrode 26 connected to a conventional EKG"red" wire is placed over the right hand. An electrode 28 connected to aconventional EKG "green" wire is placed over the left leg. An electrode30 connected to a conventional EKG "black" wire is placed over the rightleg.

These electrodes 22-30 generate time-dependent electrical analogsignals, as represented by block 32 in FIG. 2. These signals are fedinto and combined in a novel manner in combiner network 34 which isshown in detail in FIG. 3. The combiner network 34 combines theaforementioned five EKG signals into a pair of output signals at outputs36, 38. The output signal at output 36 is conventionally designatedhereinafter as "lead V5" and is indicative of the activity of the leftventricle. This analog signal is shown in FIG. 5 wherein amplitude isplotted against time. The FIG. 5 graph shows left ventricular activityfor ten seconds. The output signal at output 38 is conventionallydesignated hereinafter as "lead II" and is indicative of the activity ofa broad area of the heart. The various input signals from electrodes22-30 are amplified in differential amplifiers A1-A4, and switched byswitching circuits S1-S4, before being again amplified and conductedalong two independent paths, one oath being comprised of differentialamplifiers A5-A7, and the other path being comprised of differentialamplifiers A8-A10.

As best shown in FIG. 2, the output analog EKG signals at outputs 36, 38are sampled and digitized in an analog-to-digital converter 40. Thedigital signals are processed by a programmed microcomputer or signalprocessor 42. The results of the signal processing, as described below,are displayed on monitor 14 or printed by printer 16.

An overview of the signal processing is depicted in FIG. 4. The digitalEKG signals from outputs 36, 38 are fed to function blocks 44, 46, 48,50, 52 and 54 wherein the power spectrum, phase angle, impulse response,amplitude histogram, coherence and cross-correlation are respectivelymathematically determined. In a preferred embodiment, all of thesefunctions are determined and used in making the diagnosis. However, itis sufficient if at least two of these functions are determined. Thechoice of function to be determined at any particular time is selectedby a function selector 56 which advantageously is a function key on thekeyboard 12. Once mathematically determined, any particular function canbe displayed as an analog waveform on the monitor 14.

The power spectrum function 44 is calculated as follows: The auto powerspectrum G_(xx) (f) for lead V5 is determined from equation (1):

    G.sub.xx (f)=S.sub.x (f)·S.sub.x (f)*             (1)

where S_(x) (f) is the Fourier transform of the time-dependent, lead V5signal f_(x) (t) depicted in FIG. 5, and

where S_(x) (f)* is the complex conjugate. The power spectrum G_(xx) (f)for a patient under test is depicted in FIG. 6 wherein power is plottedagainst frequency.

The auto power spectrum G_(yy) (f) for lead II is determined fromequation (2):

    G.sub.yy (f)=S.sub.y (f)·S.sub.y (f)*             (2)

where S_(y) (f) is the Fourier transform of the time-dependent, lead IIsignal f_(y) (t), and

where S_(y) (f) is the complex conjugate. The power spectrum G_(yy) (f)for a patient under test is depicted in FIG. 7 wherein power is plottedagainst frequency.

The phase angle function 46 is calculated as follows: First, theamplitude ratio of the transfer function H_(xy) (f) is determined fromequation (3):

    H.sub.xy (f)=G.sub.xy (f)/G.sub.xx (f)                     (3)

where the cross power spectrum

    G.sub.xy (f)=S.sub.x (f)·S.sub.y (f)*             (4)

and where G_(xx) (f) is obtained in equation (1).

Second, the phase angle θ_(xy) (f) of the transfer function H_(xy) (f)is determined from equation (5):

    θ.sub.xy (f)=tan.sup.-1 {[IM(H.sub.xy (f))]/[RE(H.sub.xy (f))]}(5)

where IM and RE are the real and imaginary parts of the transferfunction.

The phase angle is a measure of the time difference between the leftventricular (lead V5) and whole heart signals (lead II) and is depictedin FIG. 8 wherein phase in degrees is plotted against frequency. Phaseleads and lags are respectively indicated above and below the referenceline.

The impulse response function 48 is calculated as follows: The impulseresponse IH_(x) (f) is determined from equation (6):

    IH(f)=F.sup.-1 H.sub.xy (f)                                (6)

where F⁻¹ is the inverse Fourier transform of the transfer functionH_(xy) (f) defined in equation (3).

The impulse response is a measure of the output response of the heart(lead II) solely in response to the input of the left ventricular signal(lead V5) and is depicted in FIG. 9 wherein amplitude is plotted againstimpulse time.

The amplitude histogram function 50 is a standard statistical analysisof the amplitudes present in the left ventricular (lead V5) and wholeheart signals (lead II) and are respectively depicted in FIGS. 10 and 11wherein the occurrence frequency is plotted against specific amplitudes.These plots indicate how many times a given amplitude is present in theleft ventricular (lead V5) and whole heart signals (lead II).

The coherence function 52 is calculated as follows: The coherence γ_(xy)(f) is determined from equation (7):

    γ.sub.xy (f)=G.sub.xy (f)/G.sub.xx (f)·G.sub.yy (f)(7)

where G_(xy) (f), G_(xx) (f) and G_(yy) (f) are defined in equations(4), (1) and (2). The coherence is depicted in FIG. 12 wherein coherenceis plotted against frequency.

The cross correlation function 54 is calculated as follows: The crosscorrelation φ_(xy) (τ) is determined from equation (8): ##EQU1## wheref_(x) (t) and f_(y) (t) are the left ventricular (lead V5) and wholeheart signals (lead II), where τ is the delay time between the signals,and where T is the test period, typically 150 seconds. The crosscorrelation is a measure of the correspondence of the signals and isdepicted in FIG. 13 wherein cross correlation is plotted against thedelay time.

Returning to FIG. 4, after the functions 44-54 have been calculated,they may be sequentially displayed on the monitor for evaluation by atechnician, or, preferably, the function waveforms, as depicted in FIGS.6-12, are stored in a random access memory and subjected to a battery oftests in which the presence or absence of various indices arerecognized. These indices all relate to the overall shape of the variousfunction waveforms and are established in advance. Each function has itsown individual pre-set indices as represented by blocks 58-88 in FIG. 4.Each of these indices has two states. A positive state indicates anabnormal condition. A negative state indicates a normal condition. Therecognition of the indices occurs in a pattern recognition program asrepresented by blocks 70-80. The pre-set indices are set forth below foreach function for an EKG analysis:

(I) Power Spectrum

(1) 1/2--Is the amplitude ratio of the first peak/second peak above alimit?

(2) O--Is shape of any of first four peaks rounded similar to omega (Ω)?

(3) U1--Do any of first four peaks have a twinned peak?

(4) U2--Are the intervals between any of first four peaks unequal?

(5) U3--Is the inequality of the intervals between any of the first fourpeaks above a limit?

(6) U3_(xy) --Same as U3 but are any two peaks simultaneously positive?

(7) U4--Is the shape of any peak similar to a hill ()?

(8) U5--Is the shape of any peak similar to a mountain ()?

(9) N1--Is the first peak null?

(10) N3--Is the third and/or fourth peak null?

(11) S--Is the heart rate below 60 beats per minute?

(12) SS--Is the heart rate below 50 beats per minute?

(13) F--Is the heart rate over 100 beats per minute?

(14) FF--Is the heart rate above 120 beats per minute?

(15) A1--Is the amplitude of the first peak above a limit?

(16) A2--Is the amplitude of any two of the first four peaks above alimit?

(17) A3--Is the amplitude of the second peak above a limit?

(18) A4--Is the amplitude of the third and/or fourth peak above a limit?

(19) A5--Is any one of the 5th-12th peaks higher than the first peak?

(20) A55--Are any two of the 5th-12th peaks higher than the first peak?

(21) A6--Are more than two of the 5th-12th peaks higher than the firstpeak?

(22) Nn--Are the first and second peaks higher than the third and fourthpeaks?

(23) nN--Are the third and fourth peaks higher than the first and secondpeaks?

(24) Nnn--Is the first peak higher than the second, third and fourthpeaks?

(25) nnN--Is the first peak lower than the second, third and fourthpeaks?

(IT) Phase Angle

(26) P+--Does the phase angle lag above a limit at various frequencybands?

(27) P--Does the phase' angle lead above a limit at various frequencybands?

(28) WW--Is the shape of the waveform similar to the letter "W" atvarious frequency bands?

(29) PW+--Do indices 26 and 28 co-exist at various frequency bands?

(30) PW--Do indices 27 and 28 co-exist at various frequency bands?

(31) L--Is the phase angle too small plus is the impulse response tooeven?

(32) U--Does the waveform have the shape of the letter "U" at variousfrequency bands?

(33) W--Are there two or more U-shaped waves?

(34) V--Does the waveform have a long upward slope?

(35) Y--is the slope of the waveform positive or negative?

(36) X--Do indices 32 and 35 or 32 and 33, co-exist?(37) Z--Does thewaveform have waves shaped like the letter "Z"?

(III) Impulse response

(38) D1--Does the waveform have a double top plane wave resembling or ?

(39) D2--Does the waveform have a stair steps wave resembling ?

(40) f--Is the main response impulse negative?

(41) M1--Does the main response impulse have a twin peak?

(42) M2--Does the shape of the main response impulse resemble the letter"M"?

(43) M3--Does the main response impulse have more than three peaks?

(44) M4--Does the main response impulse have a peak that is too wide?

(45) M5--Does the side response have a peak whose amplitude is above alimit?

(46) M6--Is the main response impulse totally downward?

(IV) Coherence

(47) Q1--Is the coherence of the first peak of the power spectrum belowa limit?

(48) Q2--Is the coherence of the highest peak of the transfer functionbelow a limit?

(V)Amplitude Histogram

(49) V+--Is the amplitude of lead V5 above a limit?

(50) 2+--Is the amplitude of lead II above a limit?limit?

(52) 2--Is the amplitude of lead II below a limit?

(53) Vn+--Is the number of bundles of the column in the amplitudehistogram of lead V5 above a limit?

(54) Vn--Is the number of bundles of the column in the amplitudehistogram of lead V5 below a limit?

(55) 2n+--Is the number of bundles of the column in the amplitudehistogram of lead II above a limit?

(56) 2n---Is the number of bundkes of the column in the amplitudehistogram of lead II below a limit?

(VI) Cross Correlation

(57) RRR--Is the amplitude of the main peak above a limit?

(58) rrr--Is the amplitude of the main peak below a limit?

(59) R--Is the main peak within a higher zone?

(60) r--Is the main peak within a lower zone?

(61) RR--Is the interval betwee R1 and R2 above a limit?

(62) rr--Is the interval between R1 and R2 too short?

(63) rR--Is the peak R1 lower than the peak R2?

(64) R2--Is the peak R2 below a limit?

(65) R+--Does the peak R1 shift to the right side?

(66) R--Does the peak R2 shift to the left side?

(67) Rw+--Is the bottom of the first positive peak below the bottom ofthe first negative peak, and so on for successive peaks?

(68) Rw ---Is the bottom of the first positive peak above the bottom ofthe first negative peak, and so on for successive peaks?

(69) pt--Is the number of peaks whose amplitude is above a thresholdbetween peaks R1 and R2 above a limit?

(70) PT--Is there one or more peaks between peaks R1 and R2 higher thanpeak R2 above a limit?

(71) Rn--Does R2 have a twin peak or a zigzag shape?

(72) Rm--Is the peak R1 too wide?

(73) Rv--Is one bend of R1 too steep in slope?

Once the state of each index has been recognized, an integrated pattern82 is generated. The integrated pattern contains the states of theindices from at least two, if not all the above functions. Theintegrated pattern 82 can be printed out by the printer as set forth inthe sample cardiogram analysis printout depicted in FIG. 14.

The printout is subdivided into three parts. A first part 84 containspatient data 90 entered via the key-board 12. A second part 86 containsthe aforementioned six functions together with the individual indexlegends and the results (+) or (-) of thee index recognition. Some ofthe indices as set forth above have been deleted from FIG. 14 for easeof illustration. A third part 88 sets forth the diagnosis which isproduced as described below.

Once the integrated pattern 82 is generated, it is fed into astatistical pattern matching program 92 to which a massive data bank isconnected. The data bank includes a multitude of index patterns takenfrom thousands of patients whose heart condition is known, usually bydirect medical examination. The index patterns of different diseaseshave different index sequences. Once the best match between the measuredintegrated pattern 82 and one of the stored patterns is obtained, adiagnosis 110 is made.

Advantageously, in the case of cardiac analysis, the data bank isseparated into eight distinctive categories, namely, ventriclehepertrophy disease 94, coronary heart disease 96, rheumatic heartdisease 98, pulmonary heart disease 100, congenital heart disease 102,myocarditis 104, myocardiopathy 106, and fibrillation 108. Thisinvention can thus distinguish between these different types of heartdiseases.

As previously mentioned, the test procedure lasts for an extended timeperiod of multiple heart and brain wave cycles. In the case of a cardiacpatient, fifteen sets of data are collected, each over a ten second timeinterval. The resultant 150-second time period has been found to besufficient from which to extract reliable data.

Returning to FIG. 4, the statistical pattern matching program 92generates a suggested diagnosis 110 and, preferably, two suggesteddiagnoses (see FIG.14, block 88, wherein the character "C" represents"coronary heart disease" and wherein the character "M" representscardiopathy"), for, presentation to a physician for use in arriving at afinal diagnosis. The number of matching indices divided by the totalnumber of indices in the integrated pattern, when multiplied by 100%,results in a "raw score". The categories of heart diseases having thetwo highest raw scores are output to the physician.

FIG. 15 depicts a technique for optimizing the suggested diagnoses. Forexample, the patient's age data 90 is entered by keyboard entry 12 and,in accordance with Tables I-V set forth below, as represented by block150, the raw scores are processed in block 152 to obtain so-called"weighted scores". The two highest weighted scores constitute theoptimized diagnoses 110 which are sent to the printer/monitor 14,16 forreview by the physician.

                  TABLE I                                                         ______________________________________                                        Coronary Heart Disease                                                        Age        Weighting Factor ± 5%                                           ______________________________________                                        <25        1.0                                                                25-46      1.1                                                                >46        1.5                                                                ______________________________________                                    

                  TABLE II                                                        ______________________________________                                        Rheumatic/Pulmonary Heart Disease                                             Age        Weighting Factor ± 5%                                           ______________________________________                                        <25        1.0                                                                25-46      1.01                                                               46         1.03                                                               ______________________________________                                    

                  TABLE III                                                       ______________________________________                                        Congenital Heart Disease                                                      Age        Weighting Factor ± 5%                                           ______________________________________                                        <25        1.2                                                                25-46      1.0                                                                >46        0.7                                                                ______________________________________                                    

                  TABLE IV                                                        ______________________________________                                        Arterial Fibrillation/Miocarditis                                             Age        Weighting Factor ± 5%                                           ______________________________________                                        <25        1.01                                                               25-46      1.01                                                               >46        1.01                                                               ______________________________________                                    

                  TABLE V                                                         ______________________________________                                        Mycardiopathy/Ventricular Hypertrophy                                         Age        Weighting Factor ± 5%                                           ______________________________________                                        <25        1.0                                                                25-46      1.1                                                                >46        1.2                                                                ______________________________________                                    

Rather than, or in addition to, using age as a weighting factor, otherparameters, such as critical information descriptive of the patient, canbe employed. For example, if the patient had a known cardiac condition,as verified by actual medical testing, prior to undergoing the diagnosisprocedure described herein, that specific medical data 90 is entered,again by keyboard entry (see FIG. 16), whereupon a weighting factor(block 150) is retrieved from memory. This weighting factor, e.g.,1.5±5% is multiplied by the raw score for that specific cardiaccondition, virtually insuring that that specific cardiac condition willbe one of the two highest weighted scores to be output to themonitor/printer.

In addition, doctors' option, also can be input into the machine, andmodify the diagnosis of the machine to make the diagnosis more accurate.

In a modification to the last-mentioned procedure, the weighting factorprocessing can be eliminated, and the specific cardiac condition can beautomatically output to the monitor/printer.

FIG. 17 is similar to FIG. 4, except that the illustrated system is nowprovided with remote transmission and reception of various signals.Rather than being in a physician's office where the arrangement of FIG.1 is physically located, the patient can be located at home or at remotesite 154 where the EKG signals 32 are sent to a transceiver 158. Thearrangement of FIG. 1 is located at the physician's office 156 and/ordiagnosis center, where another transceiver 160 is located to receivedata transmitted by transceiver 158. The transceivers 158, 160 can be atelephone line, either land-based and/or cellular, or can be a radiosignal link or, in short, any bidirectional bus. Hence, the FIC. 21system allows off-site patient testing. The transceivers can transmit orreceive analog or digital data.

The signal processor 42 of the FIG. 21 system also generates a warningsignal for transmission to transceiver 160 and, in turn, to transceiver158 and the patient in the event that the current test data exceedspre-established limits for that patient. As shown in FIG. 18, thepatient's previous test data is stored in memory (block 162), and thepatient's current test data is stored in block 164. As determined incomparator block 166, if the current data is outside the pre-establishedlimits for that patient, a warning signal is generated. Otherwise, nowarning signal is generated. This warning signal is used to warn thepatient of the presence of a medical emergency.

It will be understood that each of the elements described above, or twoor more together, also may find a useful application in other types ofconstructions differing from the types described above.

While the invention has been illustrated and described as embodied in amethod of and arrangement for optimizing heart and brain diseasediagnosis, it is not intended to be limited to the details shown, sincevarious modifications and structural changes may be made withoutdeparting in any way from the spirit of the present invention.

Without further analysis, the foregoing will so fully reveal the gist ofthe present invention that others can, by applying current knowledge,readily adapt it for various applications without omitting featuresthat, from the standpoint of prior art, fairly constitute essentialcharacteristics of the generic or specific aspects of this inventionand, therefore, such adaptations should and are intended to becomprehended within the meaning and range of equivalence of thefollowing claims.

What is claimed as new and desired to be protected by Letters Patent isset forth in the appended claims.

I claim:
 1. A method of optimizing the diagnosis of a condition of apatient tested, comprising the steps of:(a) acquiring electrocardiogram(analog signals) from the patient; (b) mathematically determining aplurality of functions descriptive of the patient from the signals; (c)establishing a set of indices for each function, each index having twostates, each indicative of the condition of the patient; (d) recognizingthe state of each index for each function; (e) generating an integratedpattern of the states of the indices from a plurality of the functions;(f) storing a collection of index patterns, each containing a multitudeof patterns of the states of indices for a multitude of patients whosecondition is known; (g) matching the generated integrated patternagainst the stored collection of index patterns to obtain a plurality ofraw scores; (h) inputting the critical diagnostic factors, which effectthe diagnosis of heart diseases, into the device; (i) establishing a setof weights for each of the critical diagnostic factors which effect thediagnosis of heart diseases, according to the importance of suchfactors; (j) weighting the raw scores to obtain weighted scores; (k)inputting doctors' opinion about the diagnosis of the patient; and (l)presenting an optimized diagnosis based on the weighted scores anddoctors' opinion.
 2. The method according to claim 1, wherein theacquiring step is performed by acquiring electrocardiographic signals asa function of time from a surface of the body of a patient beinganalyzed through a plurality of surface electrodes.
 3. The methodaccording to claim 2, wherein the acquiring step is performed byprocessing the electrocardiographic signals into two of the analogsignals that is EKG leads V5 and standard II, and the test period being100-200 seconds.
 4. An arrangement for optimizing the diagnosis of acondition of a patient tested, comprising:(a) means for acquiringelectrocardiogram (analog signals) from the patient; b) means formathematically determining a plurality of functions descriptive of thepatent from the signals; (c) means for establishing a set of indices foreach index having two states, each indicative of the condition of thepatient; (d) means for recognizing the state of each index for eachfunction; (e) means for generating an integrated pattern of the statesof the indices from a plurality of the functions; (f) means for storinga collection of index patterns, each containing a multitude of patternsof the states of indices for a multitude of patients whose condition isknown; (g) means for matching the generated integrated pattern againstthe stored collection of index patterns to obtain a plurality of rawscores; (h) means for inputting the critical diagnostic factors, whicheffect the diagnosis of heart diseases, into the device; (i) means forestablishing a set of weights for each of; the critical diagnosticfactors which effect the diagnosis of heart diseases, according to theimportance of such factors; (j) means for weighting the raw scores toobtain weighted scores; (k) inputting doctors' opinion about thediagnosis of the patient; and (l) means for presenting an optimizeddiagnosis based on the weighted scores and doctors' opinion; (m) saidestablishing means for defining indices including: (I) Power Spectrum(1)1/2--Is the amplitude ratio of the first peak/second peak above a limit?(2) O--Is shape of any of first four peaks rounded similar to omega (Ω)?(3) U1--Do any of first four peaks have a twinned peak? (4) U2--Are theintervals between any of first four peaks unequal? (5) U3--Is theinequality of the intervals between any of the first four peaks above alimit? (6) U3_(xy) --Same as U3 but are any two peaks simultaneouslypositive? (7) U4--Is the shape of any peak similar to a hill ()? (8)U5--Is the shape of any peak similar to a mountain ()? (9) N1--Is thefirst peak null? (10) N3--is the third and/or fourth peak null? (11)S--Is the heart rate below 60 beats per minute? (12) SS--Is the heartrate below 50 beats per minute? (13) F--Is the heart rate over 100 beatsper minute? (14) FF--Is the heart rate above 120 beats per minute? (15)A1--Is the amplitude of the first peak above a limit? (16) A2--is theamplitude of any two of the first four peaks above a limit? (17) A3--Isthe amplitude of the second peak above a limit? (18) A4--Is theamplitude of the third and/or fourth peak above a limit? (19) A5--is anyone of the 5th-12th peaks higher than the first peak? (20) A55--Are anytwo of the 5th-12th peaks higher than the first peak? (21) A6--Are morethan two of the 5th-12th peaks higher than the first peak? (22) Nn--Arethe first and second peaks higher than the third and fourth peaks? (23)nN--Are the third and fourth peaks higher than the first and secondpeaks? (24) Nnn--Is the first peak higher than the second, third andfourth peaks? (25) nnN--Is the first peak lower than the second, thirdand fourth peaks? (II) Phase Angle(26) P+--Does the phase angle lagabove a limit at various frequency bands? (27) P--Does the phase anglelead above a limit at various frequency bands? (28) WW--Is the shape ofthe waveform similar to the letter "W" at various frequency bands? (29)PW+--Do indices 26 and 28 co-exist at various frequency bands? (30)PW--Do indices 27 and 28 co-exist at various frequency bands? (31) L--Isthe phase angle too small plus is the impulse response too even? (32)U--Does the waveform have the shape of the letter "U" at variousfrequency bands? (33) W--Are there two or more U-shaped waves? (34)V--Does the waveform have a long upward slope? (35) Y--Is the slope ofthe waveform positive or negative? (36) X--Do indices 32 and 35 or 32and 33 co-exist? (37) Z--Does the waveform have waves shaped like theletter "Z"? (III) Impulse response(38) D1--Does the waveform have adouble top plane wave resembling or ? (39) D2--Does the waveform have astair steps wave resembling ? (40) f--is the main response impulsenegative? (41) M1--Does the main response impulse have a twin peak? (42)M2--Does the shape of the main response impulse resemble the letter "M"?(43) M3--Does the main response impulse have more than three peaks? (44)M4--Does the main response impulse have a peak that is too wide? (45)M5--Does the side response have a peak whose amplitude is above a limit?(46) M6--Is the main response impulse totally downward? (IV)Coherence(47) Q1--Is the coherence of the first peak of the powerspectrum below a limit? (48) Q2--Is the coherence of the highest peak ofthe transfer function below a limit? (V) Ampulitude Histogram(49) V+--Isthe amplitude of lead V5 above a limit? (50) 2+--Is the amplitude oflead II above a limit? (51) V--is the amplitude of lead V5 below alimit? (52) 2--Is the amplitude of lead II below a limit? (53) Vn+--Isthe number of bundles of the column in the amplitude histogram of leadV5 above a limit? (54) Vn--Is the number of bundles of the column in theamplitude histogram of lead V5 below a limit? (55) 2n+--Is the number ofbundles of the column in the amplitude histogram of lead II above alimit? (56) 2n--Is the number of bundkes of the column in the amplitudehistogram of lead II below a limit? (VT) Cross Correlation(57) RRR--Isthe amplitude of the main peak above a limit? (58) rrr--Is the amplitudeof the main peak below a limit? (59) R--Is the main peak within a higherzone? (60) r--Is the main peak within a lower zone? (61) RR--Is theinterval between R1 and R2 above a limit? (62) rr--Is the intervalbetween R1 and R2 too short? (63) rR--Is the peak R1 lower than the peakR2? (64) R2--Is the peak R2 below a limit? (65) R+--Does the peak R1shift to the right side? (66) R---Does the peak R2 shift to the leftside? (67) Rw+--Is the bottom of the first positive peak below thebottom of the first negative peak, and so on for successive peaks? (68)Rw--Is the bottom of the first positive peak above the bottom of thefirst negative peak, and so on for successive peaks? (69) pt--Is thenumber of peaks whose amplitude is above a threshold between peaks R1and R2 above a limit? (70) PT--Is there one or more peaks between peaksR1 and R2 higher than peak R2 above a limit? (71) Rn--Does R2 have atwin peak or a zigzag shape?(72) Rm--Is the peak R1 too wide? (73)Rv--Is one bend of R1 too steep in slope?